{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import net"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ip_proto</th>\n",
       "      <th>flow_duration_sec</th>\n",
       "      <th>idle_timeout</th>\n",
       "      <th>hard_timeout</th>\n",
       "      <th>packet_count</th>\n",
       "      <th>packet_count_per_second</th>\n",
       "      <th>byte_count</th>\n",
       "      <th>byte_count_per_second</th>\n",
       "      <th>entro_val</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>98</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>1.000000</td>\n",
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       "    <tr>\n",
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       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>98</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>193</td>\n",
       "      <td>96.500000</td>\n",
       "      <td>291816</td>\n",
       "      <td>145908.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>98</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425229</th>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>41</td>\n",
       "      <td>0.759259</td>\n",
       "      <td>4018</td>\n",
       "      <td>74.407407</td>\n",
       "      <td>1.719973</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425230</th>\n",
       "      <td>1</td>\n",
       "      <td>94</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>85</td>\n",
       "      <td>0.904255</td>\n",
       "      <td>8330</td>\n",
       "      <td>88.617021</td>\n",
       "      <td>1.719973</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425231</th>\n",
       "      <td>1</td>\n",
       "      <td>94</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>85</td>\n",
       "      <td>0.904255</td>\n",
       "      <td>8330</td>\n",
       "      <td>88.617021</td>\n",
       "      <td>1.719973</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425232</th>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>41</td>\n",
       "      <td>0.759259</td>\n",
       "      <td>4018</td>\n",
       "      <td>74.407407</td>\n",
       "      <td>1.719973</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425233</th>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>20</td>\n",
       "      <td>100</td>\n",
       "      <td>41</td>\n",
       "      <td>0.759259</td>\n",
       "      <td>4018</td>\n",
       "      <td>74.407407</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>425234 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ip_proto  flow_duration_sec  idle_timeout  hard_timeout  packet_count  \\\n",
       "0              1                  1            20           100             1   \n",
       "1              1                  1            20           100             1   \n",
       "2             17                  2            20           100           193   \n",
       "3              1                  2            20           100             0   \n",
       "4              1                  1            20           100             1   \n",
       "...          ...                ...           ...           ...           ...   \n",
       "425229         1                 54            20           100            41   \n",
       "425230         1                 94            20           100            85   \n",
       "425231         1                 94            20           100            85   \n",
       "425232         1                 54            20           100            41   \n",
       "425233         1                 54            20           100            41   \n",
       "\n",
       "        packet_count_per_second  byte_count  byte_count_per_second  entro_val  \\\n",
       "0                      1.000000          98              98.000000   1.000000   \n",
       "1                      1.000000          98              98.000000   1.000000   \n",
       "2                     96.500000      291816          145908.000000   1.000000   \n",
       "3                      0.000000           0               0.000000   1.000000   \n",
       "4                      1.000000          98              98.000000   1.000000   \n",
       "...                         ...         ...                    ...        ...   \n",
       "425229                 0.759259        4018              74.407407   1.719973   \n",
       "425230                 0.904255        8330              88.617021   1.719973   \n",
       "425231                 0.904255        8330              88.617021   1.719973   \n",
       "425232                 0.759259        4018              74.407407   1.719973   \n",
       "425233                 0.759259        4018              74.407407   1.500000   \n",
       "\n",
       "        type  \n",
       "0          0  \n",
       "1          0  \n",
       "2          0  \n",
       "3          0  \n",
       "4          0  \n",
       "...      ...  \n",
       "425229     0  \n",
       "425230     0  \n",
       "425231     0  \n",
       "425232     0  \n",
       "425233     0  \n",
       "\n",
       "[425234 rows x 10 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('../data/flow_stat.csv', names=['ip_proto', 'flow_duration_sec', 'idle_timeout', 'hard_timeout', \n",
    "                                                   'packet_count', 'packet_count_per_second', 'byte_count', 'byte_count_per_second',\n",
    "                                                  'entro_val', 'type'])\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 选取其中7个特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = ['ip_proto', \n",
    "            'flow_duration_sec', \n",
    "            'packet_count', \n",
    "            'packet_count_per_second', \n",
    "            'byte_count', \n",
    "            'byte_count_per_second',\n",
    "            'entro_val']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 样本均衡化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "0     12808\n",
       "1    412426\n",
       "Name: type, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(['type'])['type'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddos_data = data[data['type'] == 1].sample(frac=0.03)\n",
    "healthy_data = data[data['type'] == 0]\n",
    "\n",
    "data = pd.concat([ddos_data, healthy_data])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data.loc[:, features]\n",
    "Y = data.loc[:, 'type']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 划分训练集和测试集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "train_x, test_x, train_y, test_y = train_test_split(X, Y, test_size = 0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense (Dense)                (None, 5)                 40        \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 4)                 24        \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 1)                 5         \n",
      "=================================================================\n",
      "Total params: 69\n",
      "Trainable params: 69\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "clf = net.bpnn()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "148/177 [========================>.....] - ETA: 0s - loss: 0.5459 - accuracy: 0.8707WARNING:tensorflow:Callbacks method `on_test_batch_end` is slow compared to the batch time (batch time: 0.0000s vs `on_test_batch_end` time: 0.0010s). Check your callbacks.\n",
      "177/177 [==============================] - 0s 2ms/step - loss: 0.5283 - accuracy: 0.8743 - val_loss: 0.4436 - val_accuracy: 0.9154\n",
      "Epoch 2/50\n",
      "177/177 [==============================] - 0s 989us/step - loss: 0.3972 - accuracy: 0.9060 - val_loss: 0.3800 - val_accuracy: 0.9017\n",
      "Epoch 3/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.2787 - accuracy: 0.9145 - val_loss: 0.1986 - val_accuracy: 0.9430\n",
      "Epoch 4/50\n",
      "177/177 [==============================] - 0s 972us/step - loss: 0.1522 - accuracy: 0.9497 - val_loss: 0.1142 - val_accuracy: 0.9629\n",
      "Epoch 5/50\n",
      "177/177 [==============================] - 0s 932us/step - loss: 0.0924 - accuracy: 0.9614 - val_loss: 0.0754 - val_accuracy: 0.9688\n",
      "Epoch 6/50\n",
      "177/177 [==============================] - 0s 961us/step - loss: 0.0543 - accuracy: 0.9797 - val_loss: 0.0535 - val_accuracy: 0.9746\n",
      "Epoch 7/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0425 - accuracy: 0.9796 - val_loss: 0.0667 - val_accuracy: 0.9489\n",
      "Epoch 8/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0761 - accuracy: 0.9775 - val_loss: 0.1279 - val_accuracy: 0.9954\n",
      "Epoch 9/50\n",
      "177/177 [==============================] - 0s 983us/step - loss: 0.0873 - accuracy: 0.9936 - val_loss: 0.1024 - val_accuracy: 0.9947\n",
      "Epoch 10/50\n",
      "177/177 [==============================] - 0s 955us/step - loss: 0.0694 - accuracy: 0.9932 - val_loss: 0.0842 - val_accuracy: 0.9952\n",
      "Epoch 11/50\n",
      "177/177 [==============================] - 0s 977us/step - loss: 0.0565 - accuracy: 0.9937 - val_loss: 0.0698 - val_accuracy: 0.9952\n",
      "Epoch 12/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0459 - accuracy: 0.9938 - val_loss: 0.0581 - val_accuracy: 0.9954\n",
      "Epoch 13/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0369 - accuracy: 0.9941 - val_loss: 0.0481 - val_accuracy: 0.9956\n",
      "Epoch 14/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0296 - accuracy: 0.9947 - val_loss: 0.0398 - val_accuracy: 0.9960\n",
      "Epoch 15/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0236 - accuracy: 0.9948 - val_loss: 0.0330 - val_accuracy: 0.9963\n",
      "Epoch 16/50\n",
      "177/177 [==============================] - 0s 955us/step - loss: 0.0188 - accuracy: 0.9955 - val_loss: 0.0271 - val_accuracy: 0.9968\n",
      "Epoch 17/50\n",
      "177/177 [==============================] - 0s 977us/step - loss: 0.0152 - accuracy: 0.9968 - val_loss: 0.0222 - val_accuracy: 0.9970\n",
      "Epoch 18/50\n",
      "177/177 [==============================] - 0s 949us/step - loss: 0.0127 - accuracy: 0.9970 - val_loss: 0.0186 - val_accuracy: 0.9970\n",
      "Epoch 19/50\n",
      "177/177 [==============================] - 0s 938us/step - loss: 0.0107 - accuracy: 0.9971 - val_loss: 0.0152 - val_accuracy: 0.9974\n",
      "Epoch 20/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0090 - accuracy: 0.9978 - val_loss: 0.0122 - val_accuracy: 0.9983\n",
      "Epoch 21/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0091 - accuracy: 0.9972 - val_loss: 0.0123 - val_accuracy: 0.9960\n",
      "Epoch 22/50\n",
      "177/177 [==============================] - 0s 972us/step - loss: 0.0093 - accuracy: 0.9962 - val_loss: 0.0117 - val_accuracy: 0.9950\n",
      "Epoch 23/50\n",
      "177/177 [==============================] - 0s 955us/step - loss: 0.0080 - accuracy: 0.9976 - val_loss: 0.0113 - val_accuracy: 0.9983\n",
      "Epoch 24/50\n",
      "177/177 [==============================] - 0s 949us/step - loss: 0.0067 - accuracy: 0.9985 - val_loss: 0.0106 - val_accuracy: 0.9962\n",
      "Epoch 25/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0080 - accuracy: 0.9965 - val_loss: 0.0099 - val_accuracy: 0.9951\n",
      "Epoch 26/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0074 - accuracy: 0.9974 - val_loss: 0.0087 - val_accuracy: 0.9983\n",
      "Epoch 27/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0055 - accuracy: 0.9988 - val_loss: 0.0065 - val_accuracy: 0.9984\n",
      "Epoch 28/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0085 - accuracy: 0.9953 - val_loss: 0.0085 - val_accuracy: 0.9951\n",
      "Epoch 29/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0267 - accuracy: 0.9921 - val_loss: 0.0963 - val_accuracy: 0.9954\n",
      "Epoch 30/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0569 - accuracy: 0.9944 - val_loss: 0.0670 - val_accuracy: 0.9955\n",
      "Epoch 31/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0424 - accuracy: 0.9944 - val_loss: 0.0543 - val_accuracy: 0.9955\n",
      "Epoch 32/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0351 - accuracy: 0.9944 - val_loss: 0.0464 - val_accuracy: 0.9955\n",
      "Epoch 33/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0302 - accuracy: 0.9944 - val_loss: 0.0408 - val_accuracy: 0.9955\n",
      "Epoch 34/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0267 - accuracy: 0.9944 - val_loss: 0.0367 - val_accuracy: 0.9955\n",
      "Epoch 35/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0240 - accuracy: 0.9944 - val_loss: 0.0333 - val_accuracy: 0.9955\n",
      "Epoch 36/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0215 - accuracy: 0.9946 - val_loss: 0.0305 - val_accuracy: 0.9960\n",
      "Epoch 37/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0193 - accuracy: 0.9948 - val_loss: 0.0279 - val_accuracy: 0.9960\n",
      "Epoch 38/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0173 - accuracy: 0.9949 - val_loss: 0.0256 - val_accuracy: 0.9960\n",
      "Epoch 39/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0154 - accuracy: 0.9952 - val_loss: 0.0234 - val_accuracy: 0.9964\n",
      "Epoch 40/50\n",
      "177/177 [==============================] - 0s 989us/step - loss: 0.0137 - accuracy: 0.9964 - val_loss: 0.0211 - val_accuracy: 0.9966\n",
      "Epoch 41/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0121 - accuracy: 0.9969 - val_loss: 0.0192 - val_accuracy: 0.9972\n",
      "Epoch 42/50\n",
      "177/177 [==============================] - 0s 983us/step - loss: 0.0108 - accuracy: 0.9972 - val_loss: 0.0171 - val_accuracy: 0.9970\n",
      "Epoch 43/50\n",
      "177/177 [==============================] - 0s 989us/step - loss: 0.0097 - accuracy: 0.9972 - val_loss: 0.0152 - val_accuracy: 0.9970\n",
      "Epoch 44/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0086 - accuracy: 0.9972 - val_loss: 0.0134 - val_accuracy: 0.9974\n",
      "Epoch 45/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0075 - accuracy: 0.9978 - val_loss: 0.0114 - val_accuracy: 0.9984\n",
      "Epoch 46/50\n",
      "177/177 [==============================] - 0s 983us/step - loss: 0.0065 - accuracy: 0.9985 - val_loss: 0.0098 - val_accuracy: 0.9984\n",
      "Epoch 47/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0058 - accuracy: 0.9988 - val_loss: 0.0082 - val_accuracy: 0.9985\n",
      "Epoch 48/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0051 - accuracy: 0.9990 - val_loss: 0.0070 - val_accuracy: 0.9984\n",
      "Epoch 49/50\n",
      "177/177 [==============================] - 0s 983us/step - loss: 0.0047 - accuracy: 0.9989 - val_loss: 0.0060 - val_accuracy: 0.9984\n",
      "Epoch 50/50\n",
      "177/177 [==============================] - 0s 1ms/step - loss: 0.0054 - accuracy: 0.9982 - val_loss: 0.0063 - val_accuracy: 0.9974\n"
     ]
    }
   ],
   "source": [
    "history = clf.fit(train_x, train_y, epochs=50, validation_data=(test_x, test_y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "787/787 [==============================] - 0s 615us/step - loss: 0.0055 - accuracy: 0.9979\n"
     ]
    }
   ],
   "source": [
    "# 模型评估\n",
    "clf.evaluate(X, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 保存模型\n",
    "clf.save()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 一些图表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['loss', 'accuracy', 'val_loss', 'val_accuracy'])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "history.history.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "acc = history.history['accuracy']\n",
    "val_acc = history.history['val_accuracy']\n",
    "\n",
    "loss = history.history['loss']\n",
    "val_loss = history.history['val_loss']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [i for i in range(1, 51)]\n",
    "\n",
    "plt.figure(dpi=200)\n",
    "\n",
    "plt.plot(x, acc, label='Train Accuracy')\n",
    "plt.plot(x, val_acc, label='Validation Accuracy')\n",
    "plt.xlabel('Epoch Number')\n",
    "plt.ylabel('Value of Accuracy')\n",
    "plt.title('Epoch-Accuracy Line Chart')\n",
    "plt.legend(loc='lower right')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [i for i in range(1, 51)]\n",
    "\n",
    "plt.figure(dpi=200)\n",
    "\n",
    "plt.plot(x, loss, label='Train Loss')\n",
    "plt.plot(x, val_loss, label='Validation Loss')\n",
    "plt.xlabel('Epoch Number')\n",
    "plt.ylabel('Value of Loss')\n",
    "plt.title('Epoch-Loss Line Chart')\n",
    "plt.legend(loc='upper right')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ROC曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay, accuracy_score, f1_score, classification_report, roc_auc_score\n",
    "from sklearn.metrics import roc_curve, auc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.21008658"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions = clf.predict(test_x)\n",
    "\n",
    "fpr, tpr, thersholds = roc_curve(test_y, predictions, pos_label=1)\n",
    "roc_auc = auc(fpr, tpr)\n",
    "\n",
    "maxindex = (tpr-fpr).tolist().index(max(tpr-fpr))\n",
    "thersholds[maxindex]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "th_x = fpr[maxindex]\n",
    "th_y = tpr[maxindex]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(dpi=200)\n",
    "plt.plot(fpr, tpr, 'k--', label='AUC = {0:.4f}'.format(roc_auc), lw=2)\n",
    "plt.xlim([-0.05, 1.05])\n",
    "plt.ylim([-0.05, 1.05])\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('BPNN ROC Curve')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.plot(th_x, th_y, marker='o', color='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [i for i in range(1, len(thersholds) + 1)]\n",
    "\n",
    "plt.figure(dpi=200)\n",
    "\n",
    "plt.plot(x, fpr, label='False Positive Rate')\n",
    "plt.plot(x, tpr, label='True Positive Rate')\n",
    "\n",
    "plt.axvline(maxindex, ymin=fpr[maxindex], ymax=tpr[maxindex], color='black', linestyle='-.', lw=0.5)\n",
    "\n",
    "plt.title('TPR-FPR Line Chart')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "49"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxindex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:newpy]",
   "language": "python",
   "name": "conda-env-newpy-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
